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Predator Technical Report Report DEQ08-LAB-0048-TR PREDATOR: Development and use of RIVPACS-type macroinvertebrate models to assess the biotic condition of wadeable Oregon streams (November 2005 models) By: Shannon Hubler July 2008 Last Update 07/14/2008 DEQ08-LAB-0048-TR Version 1.1 Web pub#: 10-LAB-004 This report prepared by: Oregon Department of Environmental Quality Laboratory and Environmental Assessment Division Watershed Assessment Section 3150 NW 229th, Suite 150, Hillsboro, Oregon 97124 U.S.A. 1-800-452-4011 www.oregon.gov/deq Contact: Shannon Hubler (503) 693-5728 1 List of Tables ...................................................................................................................... 3 List of Figures ..................................................................................................................... 3 Rationale ............................................................................................................................. 4 What is a Predictive Model? ............................................................................................... 4 Why Macroinvertebrates? ................................................................................................... 4 The PREDictive Assessment Tool for Oregon (PREDATOR) .......................................... 5 How does a predictive model differ from a Multi-metric approach? ................................. 5 Developing the Models ....................................................................................................... 5 Macroinvertebrate Sampling Protocols ............................................................................... 6 Taxonomy ........................................................................................................................... 6 Model Development ............................................................................................................ 8 Null Models ........................................................................................................................ 9 Final Model Selection ....................................................................................................... 10 Assessing model quality ................................................................................................... 13 Comparisons to other PNW RIVPACS-type models........................................................ 13 Null model performance ................................................................................................... 16 Using the models............................................................................................................... 16 PREDATOR outputs ......................................................................................................... 16 Benchmarks of biological condition ................................................................................. 19 Population Assessments .................................................................................................... 20 Individual site assessments ............................................................................................... 21 Causes of poor biological condition ................................................................................. 23 The importance of assessing multiple assemblages .......................................................... 25 Conclusions ....................................................................................................................... 26 Future versions of PREDATOR ....................................................................................... 26 Recommendations and Needs ........................................................................................... 27 Acknowledgements ........................................................................................................... 28 Literature Cited ................................................................................................................. 28 Appendix A. ...................................................................................................................... 31 Appendix B. ...................................................................................................................... 44 Appendix C. ...................................................................................................................... 46 2 List of Tables Table 1. A hypothetical example of how consistent taxonomic levels are achieved. ......... 7 Table 2. PREDATOR model specifications for three regions in Oregon. ....................... 11 Table 3. PREDATOR 2005 model performance statistics.. ............................................ 14 Table 4. O/E benchmarks for describing biological condition for predictive PREDATOR models. ...................................................................................................................... 19 Table 5. Benchmarks for describing biological condition for the null PREDATOR model......................................................................................................................... 19 Table 6. OTUs and phylogenetic classifications used in PREDATOR models. .............. 31 Table 7. Candidate predictor variables that were examined in PREDATOR model development. ............................................................................................................. 44 Table 8. MWCF reference sites and corresponding environmental data ......................... 46 Table 9. WC+CP reference sites and corresponding environmental data ....................... 47 List of Figures Figure 1. PREDATOR consists of two predictive models and one null model ............... 12 Figure 2. Performance of the MWCF model and of the WC+CP model. ........................ 15 Figure 3. Frequency distributions of O/E scores for samples assessed by the MWCF model........................................................................................................................ 18 Figure 4. The extent of biotic condition classes for samples in the Coast Range ecoregion and the Willamette Valley ecoregion ....................................................................... 22 Figure 5. Identifying potential causes of impairment in two sites with O/E in most disturbed condition................................................................................................... 24 3 Rationale The Oregon Department of Environmental Quality (DEQ) is responsible for protecting the waters of the state from pollution that may adversely affect drinking water, aquatic life and recreational uses. DEQ routinely monitors conventional water quality parameters such as nutrients, dissolved oxygen, pH, turbidity, conductivity and bacteria to report on the water quality status and trends in Oregon. However, resource limitations make it impractical to measure all the potential pollutants which may impair Oregon’s waters. Aquatic insect communities are direct indicators of biological conditions and a surrogate for watershed health. They provide a cost effective screening tool for assessing and identifying problems that may require further examination. The purpose of this document is to provide a background on predictive modelling, its utility, and the specific application of the macroinvertebrate models used by the Oregon DEQ. What is a Predictive Model? A predictive model, in this case, is a tool used to assess the integrity of an aquatic insect assemblage. Predictive modelling estimates the expected occurrence of macroinvertebrates at a sample location. This is done by developing a list of insect species that commonly occur at least disturbed, or reference, locations that have similar natural characteristic to the sample locations. The list of species generated from the reference locations is known as the “Expected” taxa list or “E”. This list is compared to the captured aquatic insects or,“Observed” taxa (“O”), at an assessment site. The predictive model output is the observed to expected (O/E) taxa ratio. Scores less than one have fewer taxa at a site than were predicted by the model. Scores greater than one are either equivalent to the reference location or may have an enhanced insect community as a result of some type of enrichment. Another way to think of the score is in terms of the percentage of taxa loss or gain. Values less than 1.0 represent a loss of common native reference taxa. Percent taxa loss or gain is defined as: (O/E – 1.0) * 100 A negative value means a sample has lost reference taxa, while a positive value means the sample has gained reference taxa Why Macroinvertebrates? Macroinvertebrates include freshwater insects, crustaceans, mollusks, bivalves and other invertebrates larger than one half millimeter in size. They are important because they occupy a central role in food chains and ecosystem processes (Wallace and Webster 1996). Macroinvertebrates are easy to collect, are relatively cheap to process and analyze, and show strong responses to many stressors. These benefits, make macroinvertebrates the most commonly used aquatic organisms for assessing stream biological integrity. For a thorough examination of the role of macroinvertebrates in assessing biological integrity, see Rosenberg and Resh (1993) and Wright et. al (2000). 4 The PREDictive Assessment Tool for Oregon (PREDATOR) PREDATOR consists of three regional models that assess the biological integrity of wadeable streams across Oregon. DEQ developed the models to supply a scientifically
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